Key takeaways

The data model itself is straightforward; the key is to understand how the model is built to support growth loops, closed loops systems, and revenue processes.

The topics that we step through in this workshop include:

  1. The bowtie as a full-funnel model
  2. How the bowtie supports growth loops, and the need to create a closed-loop system
  3. A customer-centric data model based on customers achieving recurring impact, which then results in recurring revenue
  4. The three types of metrics that every recurring revenue team should be measuring: volume metrics, time metrics, and conversion metrics

Additional insights and key findings from this workshop: 

a) how to use benchmark data and apply it to your own model

b) the application of various GTM models and associated metrics

c) how to use performance metrics in practice

Hi, my name is Jacco van der Kooij. I'm the CEO of Winning By Design. And I love music. Oh. And I also love sales. Yes, I do. And today I'm gonna share with you the data model. And what we can do of the day tomorrow. You ready? Now over the past weeks, we have been talking about a few of these business models. I don't know if you have followed us on our YouTube channel, but up to this point we have been discussing these three models. The business model, the GTM model and the growth stage model. And as promised, we will step model by model and we're gonna go through all of them. The next one up is the data model. That's where we're going to start today, the data model. And I wanna share with you some of these changes that have occurred over the past years. Now, what we see through this data model, is that historically we're used to a funnel. This funnel that all of you know, it's a little bit historic, okay? Yeah. That kind of historic. Okay. And what we see in this model, that has been put together by Crystal Ball, Sages, it feels like wizardry, okay? And this wizardry is applied to different parts as if we are using like some magic to turn prospects into pipeline. That makes many of us think that it's an art. Now what we see here in this art is divided in three pieces, three parts; pipeline conversion, often done by sales, pipeline development done by teams of prospecting, or by content, or by marketing teams, and pipeline creation often done by the marketing function. But I have to tell you. It is time to move on from this. This approach to looking at customers as if we are generating revenue and we are just popping them out, is outdated. And that's why we're gonna take a look at the new model. And this new model has a relatively new approach. ♪ Where do we go from, where do we go from ♪ We're going look at what we call the Bowtie. ♪ No one can save us ♪ And this bowtie is based on science, proper modeling. ♪ I don't wanna lose you, I don't wanna lose you ♪ The idea is that you don't want to lose a customer, once you've signed them. You wanna keep them with you, and you wanna help them achieve the impact that they wanted from you. ♪ Hey, hey, hey ♪ ♪ I just wanna say you're my new crave ♪ That's it. We want them to be craving. They want them to love it. ♪ Hey, hey, hey ♪ ♪ I just wanna say you are my new crave ♪ ♪ Before you turn around ♪ Yes, yes, yes. And so what I'm gonna take a look at, is I'm gonna take you through what a modern funnel can look like. Now, a model funnel is based on these five key elements, four key elements. I'm gonna take you through how it's full funnel, how it has closed loops in there, how it is customer centric, what specific data we're gonna measure. And we're gonna share with you some findings. So let's get going on that. What we're gonna see that historically, the bowtie, what we're looking to complete is making it full funnel. I'm gonna draw from the single funnel. What we see down here is not full. I'm gonna tip it to its side. Boom. And we're gonna see that that process historically is there to sell products to customers. Think of routers, think of like, yeah like equipment and so on and so forth. Now, what we see here at the left, and we have prospects coming in on left, and closed/won deals on the right. In order to close them, we have a very seller perspective, we call about negotiating, targeting, winning, objection handling, selling, and so on. And all that is, it is as if we are focused at closing the deal and being done with them. Now in order to do, we take them through three stages. Those stages are; create the awareness. You know what? It could be with a billboard. It could be an advertisement in a magazine. It could be with content online. It could be with targeting them with content on LinkedIn based on persona. What we then do is we see, educate them. We educate them with content. What are the options to have them learn more about the problems they're running into. To have them learn more about the solutions that are out there. And then what we see is they're gonna make a selection. They are gonna deem this as important and once it is important it becomes a priority. They're gonna spend money and resources in order to achieve the desired impact. That is from a very customer perspective. Hey, I become aware. I educate, I become educated and therefore I now know what I want. And I'm gonna make a selection and come to a decision. What is still here at the bottom is, prospects to sell to and closed/won, that is still very seller centric. Imagine what is it like, It feels like there's an end. Once I close here, closed/won, boom! The end. Thank you very much. Can you imagine let's pay the end credits. Thank you for coming people. We closed the deal. Good luck. See ya. Bye-bye. This is not what business is like. For those of you who've been long in sales, you know, your relationship with your customers is often what you take, what you keep way longer than your relationship with the companies you represent. Now that means that we need to make this seller perspective. Now, what I'm going to do is I'm gonna lean it a little bit in on the journey and say like, hey, we started there. We come to an end. How can we change that? Well, we need to change that by not thinking about prospects as people we sell to, but as prospect as people who we can help achieving impact. Who can benefit from it. And there is no end, what you see down here. That is not a closed/won deal, but instead like a relationship, it is a start of a commitment. We are mutually committing to something. Now, this makes it no longer the end to stay in the movie theme. The end of the movie, we're just entering the intermission. Get your popcorn, get settled. Talk a little bit about the, you know, like what you think who did it in the movie, because it is gonna get on. And what you see down here. Yeah. Like, I don't know about you, but whenever I'm in a cinema, I saw the other day Tenant, great movie. But what I found is that, you know, like your popcorn. Yeah. You're done with the popcorn even before the movie starts. Sidebar, sidebar, sidebar, you know. Like little I can say about that other than, Okay. Good. What we now gonna do, we're gonna go, continue the journey. So no longer is there an end. We're coming back from intermission. Now what? Now, what we're going to do, is we're gonna see that there's an entire new funnel coming to the right. And that right, we're going to focus on right now. That is really where we're going. That is where are we going from here, okay? I want you to realize, that's the one that we want. That's where we're gonna go to. Now, in order to do that, I'm gonna make sure that we're gonna go through a few stages, that actually are really similar to what we see on the sales site. These three stages that we're gonna go through is activate slash onboarding. For people who selling applications, think of a Chrome plugin, that's activation. But if you sell a CRM platform or security platform you're probably thinking about onboarding. Now, sometimes that can take you know, minutes, seconds, days, weeks, months. But it's gonna end up with the client having a working platform. A platform that works as advertised, is delivered as promised, within budget and on time. Now, what we see once that platform application is performing, it delivers the impact that the client wants. That impact is the reason why you start to recurring revenue stream. And as you grow your business, you achieve the maximum impact over the lifetime value of that client. That means that on the right, the vertical axis, depicts the impact that was delivered, the maximum impact. And on the left, the total available market is not like how many people are out there, but how many people your product can impact the business. That creates a full funnel approach. As I promised that I would demonstrate to you. Whoo! We now know the bowtie is a full funnel. It's full funnel. It goes, marketing sales, prospecting, customer success, onboarding, account management, everything. Next one I'm gonna step into, is explain to you, how they're a loops inside that full funnel. Where there are loops, creating occasionally a closed loop system. Now, what we're going to take a look, is we're gonna take a look at the same model, as you see down here. And you see the client journey as the client maneuvers through stages, you know, like meetings, discovery calls, demonstrations, proof of concepts dependent on the size of the deal, and what not. As it comes through that journey it ends, and you know, like the first thing that I start notice is, is this journey really linear? Look at that. Is it linear? Second is, it's like, hey, my gosh. Is there only one way we can go? And the third question is, is this truly the end? Is there no more? This is the end of it. What you see here is a closed loop. And this loop creates a feedback on the end of a customer. Think of it as an NPS score, where a happy customer generates through a recommendation, a new lead. You can mimic this. You can create your business. You can create processes, where you'll learn who your best customers are and start, you know, like acquiring them that way. So for example, if you think of a customer that you really, really like, who has brought you lots of other customers. They were like, one of those customers that unlocked a whole bunch, a whole new segment of customers. Had you known that at the beginning of the journey, you would have been probably willing to spend a lot more you know, marketing dollars and sales support dollars on that, to acquire them. Acquiring those kind of clients would find you willing to increase the client acquisition costs. That creates a form of a closed loop system if you would note that. Now what is closed loop? And I wanna draw it as an analogy down here. A closed loop can be thought of when you're driving your car. It was not too long ago, that you can create cruise control. And cruise control is where you essentially like, you start, you know, like programming the speed of your car. There's no radar in your car. And when you program at the 65 miles an hour, it will be going 65 miles an hour until you run out of gas. And in the beginning, that was quite fine. Or bump into something. Yes, I get that too. And so you know, that is cruise control. You program the speed. Now, that is an open loop system. It is not responsive to what is happening all around it. Now, what I'm going to create, is I'm going to create a closed loop system. I'm gonna create some feedback loop in there. That feedback loop, I'm creating through radar. And when I use radar, I'm measuring the distance to the next car. And as I see the distance decreasing, I'm starting to adjust speed. That is a closed loop system. Now I can go very wicked with this, because what you'll can see, is what is now the difference, and how are we going to apply artificial intelligence? Artificial intelligence most of the time requires a closed loop system. If you do not have closed loop systems, there is no, you don't even need to talk about AI. There's just a little use for it. AI learns from closed loop system. That's the whole nature from learning on itself. And as I let you read these blocks here, you're gonna learn what the closed loop system is. Most of the time, we're not looking at closed loop systems inside, marketing and sales operations. Almost always, they're open loop. And at best, what we gonna see is some automation. And that is what you see depicted down here. Almost all systems in the market are open loop systems. Now what we start to see when AI starts to play, think of Amazon, recognizing what you buy, applying what other people have bought, adding your spending power, time of day, all that, and then trying to create a closed loop system. In other words, making you a prospect for a new product to sell. These loops, you know, create smaller closed loops. And what you see down here, is these loops. In this case, for example, we see a loop like this in the sales department. Think of, in a sales department where a seller is progressing from discovery to demo to maybe a proposal. But then runs into a person, a senior executive who says like, hey, what are we spending money on? And that executive needs to go through, hey, what was the discovery process? Give me a demo before they approve. Therefore they go back into the sales journey. This going back and forth create little loops. Most CRMs are not very well suited for this. If you think of that, it means that you move your CRM forwards from stage to stage to stage. And you're, let's say you're in the proposal stage. And then suddenly you would reset it back to stages, to discovery mode. You know, like people in the organization would see that as if your opportunity has decreased in likelihood. It has improved because of the essentially steps through with a senior decision maker. This is an indication that today's CRM systems, are incapable of registering what is truly happening in the deal. And it just puts it into an advanced mode such as navigating the organization or creating decision approval or something like that. Where in true fact, it is stepping with the executive decision maker through the discovery and demo process. There are other loops. And what the loop that you see down here is the nurturing loop. This is a more well known loop, where we keep nurturing content to the database until they, you know, surpass a certain threshold and expressing interest to buy. Whether that is by contacting us. Or whether that is by visiting, for example, a pricing page or something like this. This creates a loop down here. And now that is called the nurturing loop. The problem with this nurturing loop, is that we have hit it so hard over the years that people are really overwhelmed. And so this has become less valuable in many organizations where we see that the marketing material being distributed during this process has gotten at such a volume that it no longer triggers, truly interested people. Now, this gives us a start. There is one more loop, and it's the most exciting loop of all. Here it comes. Ladies and gentlemen, this is the growth loop. This is what we're doing this for. And when I say we, I do not mean the selling organization. I mean, all of us are working towards this. This is the growth loop. And it creates compound growth as you will see in later models that I'm gonna describe. Now what you see down here, is a client, you know, you're achieving the impact, and ready to find more impact. Either they can expand the contract for another year. They can put more users on it. They can buy new product from you. This creates a growth loop. Yes, yes, yes. This growth loop is what this business is about. Now, what you've seen down here, what I've done, we now have the bowtie, full funnel model. In that model, we start to see the customer journey. The customer journey, is the journey that they take full of experiences, and they make loops and bounces. They go one way, they go two ways. And hopefully in the future, when you do your job well, they create closed loop systems. That is what we're looking for. Next step that we're gonna talk about, is how to create customer centricity. Because up to now, when we're looking at it, we still do not know, what are we selling? So, time to get going on the customer centricity. And this is one of the most exciting parts. Now what I'm going to take you through, is I'm gonna once again, use that baseline model. The bowtie. The bowtie again, is full funnel. It goes from all the way to marketing, through to sales, of prospecting sales organization, onboarding customers' access to account management. What we notice is where the power of that growth loop was. Where it created recurring revenue. And our intent as sellers in SaaS organizations, as sellers anywhere, when we sell to a customer, we love them to buy more. This is referred to as recurring revenue. It can come from an existing hardware contract where a customer buys this similar routers. It can come from software sales as a service software, as a service. It can come from anything. Now, what I'm going to do, is once that client starts creating more and more recurrence it, at a certain point in time achieves the maximum revenue possible. The client either graduates out, you know, like in let's say it's over five, six, seven years. We now have achieved lifetime value. Now the key here is the following. Look at the top. Okay. That's the point. Recurring revenue, is the result of recurring impact. Let me repeat it. Recurring revenue is the result of recurring impact. That, ladies and gentlemen, is a success to all of your SaaS business. To understand that recurring revenue, is the result of recurring impact. Why don't you arrest me right now because that essentially, is the key metric of all, okay? I'm so sorry. I'm sorry. I'm having too much. Good. I'm gonna start it out a beat. Sorry. I'm having too much fun. Okay. So we wanna achieve that recurring revenue. Now, I want you to take a look. If recurring revenue is a result of recurring impact, that means that they are interchangeable. Look at the bottom right, okay? I'm gonna gray it out, over there. Recurring revenue and maximizing revenue. That can be exchanged with the following. If I achieve recurring impact, I can tell you we gonna get recurring revenue. And if we achieve maximum impact, then we're also going to achieve maximum revenue. In other words, in order to achieve all this revenue, we simply gotta deliver the client the impact that we promised we would, right? Yeah. I mean, I cannot make it any simpler than that, right? I mean, dude, you bought an Uber ride and it dropped you off exactly where you want it to, at the time you really want it to. Wala, which is French for dare. You see? And so I'm telling you, it's that simple. Now in order to be able to deliver the impact, I'm gonna go upstream. I'm gonna go in reverse. I'm gonna go back into the funnel. Now, before I do that, I forgot, you know, impact has two kinds. We call it emotional impact, which is, you know what you normally measure. It's a form of an NPS score. Customer expresses love for you and rational impact or just money. You know, more seats, you know, more increased usage and so on and so forth. These are two kinds of impact. Now what I'm going to, I'm gonna look at the causality. That means I'm gonna go upstream and say, before I can achieve recurring impact, I gotta first be able to achieve impact a client is ready to. In other words, I need to onboard them. Now, before I can get them onboarded, I need to probably get them committed before I assign resources. So I need to get a mutual commitment signed. And before I do that, I probably, in the sales process need to engage them in a conversation around what they want to achieve. What is the impact that they want, and demo that impact. Then if I go further upstream, what we consider a lead, is like it's a person who expressed to learn more about the impact that you can achieve in that. Then if I go further, then actually a prospect is somebody whose business I can impact. That is the simplicity of this. This is it. It's not more complex. Now, what you see down here, calling your customers prospect, lead, opportunities and so on, is still a bit seller centric. So we're gonna change that. Now, the great thing is, the answer to what we should call it is staring as literally right in the face. If we remove all those sellers centric words, then you're going to see, in there, you're going to see someone who identified. Somebody who expressed interest, somebody who was engaged in it. Somebody who's committed to it. A client ready to achieve it, and so on and so forth. Simply if we highlight those words, we will get to what we are actually doing and how valuable it is. Now, I'm going to see identified. I'm gonna take that. I'm gonna take that to the top. And over there, I'm gonna create what you would refer to a historically as the customer journey. A client, we identify clients whose business we can impact. We create awareness about the impact we provide. They become interested. We help them with education on the problems to solutions, the different options that they're having. They become very engaged. As they go through the engagement process, they are picking a choice. Where there maybe one of two or three options. It may be between us and a competitor. It may be between us and no action, not deemed to be needed enough, or it maybe in an alternative way. These are all options. Finally, they commit. And as they commit, you know, like they need to activate that, you know, like in a platform it may take a week to get the platform onboard or in case of activation, it may take a few seconds. You click you install and so on and so forth. Once your option is enabled the Chrome browser plugin is working. You start to achieve the impact that you want and you achieve the impact every day, every hour every minute, every week, whatever it is. As you expand it, as you like it, you start to expand it. You want more of it. You renew the contract, weekly, monthly, annually, quarterly, whatever it is. You buy more, and you eventually end up at maximum impact. That is the impact journey. All along. You do it every day in your life. You do it whether you buy from Amazon, Starbucks, Uber, Lyft, everywhere. It's the same journey. All you do is, hey, I pay you for something, deliver me for that what I pay you for, it is that simple. Now I want to highlight some change in here. In the middle of there. For many of you who run into a platform sale, you create a little gate there. And it says like, hold on. I'm not gonna let everybody through. And the reason why that is, is because once you pass through this gate, and this is often where the sales professional accepts the client into their funnel, the client is gonna get access to, for example, experts, executives at the company, proof of concepts. You may start spending lots of time and energy on responding an RFP or an RFQ. All that takes lots of effort. And as a result, you're increasing the client acquisition cost. For you to access that, we need to make sure that the client is ready. We refer to that as a form of priority. Historically, we use that gate as if you have budget. That was the historic. That's no longer needed, because SaaS contracts often fall within budget and budget should already have been tackled long ago. SaaS companies are not buying because they don't have budget. Budget actually is not that important. Next what we did, the second generation people they made a decision based on an ROI model. Do we provide enough return on your investment? However, when we looked at ROI model, SaaS pricing, by the very nature of it, is priced at a fraction of what historically was the perpetual model. That means that we always have a positive ROI. Dude, we just dropped the costs to 20% as if you bought the software upfront. We just dropped it to 20 from 100%, you know, like perpetual software license, to a SaaS contract. You know, like whatever. We went from a million dollars a year to $20,000 a month. You bet you that the ROI is skyrocketing. Now, you're not selling just against a client with a virtual software or with hardware, you're selling against all kinds of other SaaS provider. So your ROI model doesn't make sense anymore. SaaS contracts and today's contracts are sold on, is this a priority right now? And the priority's base, is do I want this impact at this given point in time? If I look to a traditional ROI model, it doesn't take into account the element of time. It just says there is a need. And when we provide this, there is, you know, like it's a positive outcome. We deal with priority because you are selling against 20 other SaaS providers, who have an equally important ROI model that has a 10X. And so you have to determine, as a buyer, or as a buyer has to determine, is this a priority right now? Keep that in mind. This is a whole different world with selling in today. You like? Wooh! Whoo! Okay. That was a lot, okay? I, yeah, like there was a lot of nuggets in there, that I want you to think about. What we now here see, or what we now see here, is a bowtie framework that we are gonna build a data model on. We need this, because if I didn't build a proper framework first, then our data model wouldn't make sense. I first need to put in the proper fundamentals. Is it customer centric? Doesn't deliver what the client wants? Otherwise, I'm just gonna have, you know, a limited data model. But now, I have a proper data model or the fundamentals, and I can start building a data model. I'm just having too much fun. Don't you see what I see? Folks. This is what sales is about. We think that sales is about closing and objection handling. These are secondary skills. Learning what your customer really wants, the impact they want to achieve. That is the real art. What we refer to as art of sale. But it's just a science. Learn what your customer wants and deliver what they pay for. I'm telling you, I love what I do. And I love to share with you. I just hope, you're not like, you don't think I'm weird or anything. Okay. This now gives us the opportunity to actually build the data model. Okay? Now it's time. Let's build this data model. We now have full funnel, marketing sales, customer success, prospecting, onboarding, account management, everyone. We now, it's closed loop. It has a nurturing loop, it has sales loops, it has growth loops. It's looping everywhere. It is customer centric. It is built to deliver the client the impact that they want. Now, what we can do, is we can start building a data model. I'm gonna do that, I'm step you through three different metrics, starting with the first metric, volume metrics. Now, what you see with volume metrics is things we measure in volume. Think of how many leads do we have? How many opportunities are in the pipeline? How much revenue? What is the total weighted pipeline? These are all things we measure. How many seats do we have active? How many customers do we onboard? You know, like, have you onboarded last week? Volume metric. And one of the most common volume metric is, how much recurring revenue? MRR as in monthly recurring revenue, or AR as an annual recurring revenue. So let's take a look at what those data models look like. What we see down here, is we're taking a bowtie, and we're gonna look at the bottom and we're gonna define volume metrics. Look how they map up against the top. Against like, identify that interest. They all map to that, okay? That's where I'm gonna go. So now what we're gonna see, is different go-to market models of map code their volume metrics differently. In case of a two-stage sales organization, what you see down here, they're calling that MQLs and SQLs and so on and so forth. Now, if the contract closes annually, then you're gonna see ARR. What you see for example, of product-led growth, it operates at a different speed. It often, you know, talking about the sale cycle measured in days where a platform that uses a two stage sales organization as ARR and Es, often are using sales, you know, measured in weeks or sometimes even months. And so down here, what you'll see, is they use different metrics, sign up, instead of MQLs and product qualified lead, and so on and so forth. Because those contracts, in this case I assume that they're signed on a monthly contract. You're gonna see MRR as measurement M7. Now that may be very different. For example, if we are using a field sales organization, and in this case, this field sales organization is targeting and using qualified accounts instead of leads, and you know, like sales qualified accounts that are getting access to advanced resources, in this case, most likely because, you know, like, of this bigger deal size, they're gonna sign annual contracts. And that's the reason why you see those metrics there. The point down here is this data model, the volume metrics need to be defined upfront. And that is a great place to start for you. What are your volume metrics? How have you defined them? And this is a key because it provides the fundamental basis for us measuring what we're going to do. Now, as you measure, you know, as you create the process, you're going to find that, you know, it looks something like we have done here for one of our clients. At the top, you see your bow tie funnel, and then you are measuring your metrics. What is my MQL or what is my, you know marketing qualified account definition? What is my, how do I define a win? Is that a signed commitment? Or is it clicked on, you know, like a form that we have activated account? All these need to be defined. This process of defining. We recommend that you do that as a team. And then once you experience that, you're gonna find it's so great to do that. What I wanna point you to, is a mistake you will make. And that mistake, is where you are starting to look at exceptions. Yes, but what if this and that? I know I've been through many of these. Don't spend 80% of the time, discussing the exceptions. Okay? Keep it simple. Let the exception take care of itself later on. Don't try to be all inclusive, with every exception condition that you can identify. What I now have is I can define the time metrics. Now, the time metrics, you know, We have used historically, we've only used a few very common time metrics. The most common time metrics is sales cycle. And we still don't know when we start measuring it and so on and so forth. Now, the sale cycle is often, can be determined as the moment in time that the sales professional in charge of helping that client come to a mutual commitment, that they do that, in the length of time needed for that. The other one is time to life. You know, like for an application a Chrome plugin, for example, that may take seconds. Whereas, you know, like for product-led growth, that may take like a few minutes. And for installing, you know, entire CRM and replacing existing systems may take months. You know, these are a few of the metrics. What you've already noticed is that sometimes we talk about MRR, ARR, that depends on your contract. So we know, are we going month to month? Or are we going year to year or quarter to quarter? These are all the different metrics of time. And so you see down here, the 𐤃t indicates the time difference. Conversion metrics work exactly the same. Now what you see here is the, historically the conversion metrics we were using. And it's even more three letter acronyms. Because there weren't enough. Okay. Now, we have these more metrics that we're having. These stand for, lead to opportunity and opportunity to close. These are historic metrics. The problem of these metrics was they were not, they didn't give us the level of granularity that we needed. So we needed to close closer typically, because some of our higher velocity business, those metrics up front are really important. And so what you see down here, we define for that higher velocity business, we are defining, you know like more resolution converting or looking at the conversion metric of prospects in this case for example, to MQL being CR1, and conversion rate too from MQL to SQL and from clients who are interested to client being engaged, being CR2. We do the same thing with the opportunity to close. Yes. Like I said, more three letter acronyms. And in here, we're two conversion rates. This conversion rates CR3 is often referred to as the handoff rate. Is this case, the prospecting person often referred to as an SDR, sales development rep, handing it off to the AE. Then that AE, account executive sales manager, closes. And that is the close. The win rate is CR4. Now, what we want to make sure, is that if I look down here at T4 at the bottom, this is essentially the sale cycle. You always want to make sure that that sales cycle measures, aligns with the win rate. Sales cycle and win rate, go hand in hand. You cannot measure win rate from this particular metric down here, and sale cycle from another. They are measured across the exact same time span. That is a key. And you can see here why that makes sense. That means that this line, for example is an important line down here. Because as I said a second ago, that is the line that depends sales cycle. And in this case, the sales cycle and win rate, are along these lines. Now let's take a look at what other metrics are. And these metrics are very, you know, like I said, very defining in two-stage sales organization where a prospecting person, hands off the deal to a seller. These give us the four match specific metrics, the acquisition-based conversion metrics. We're now gonna take a look at the retention-based conversion metrics. Historically, we looked at churn. But churn by itself is not defined enough. Most sales organizations are looking at things like revenue churn, and so on. What we say is, before we go there, let's split up first. What is the onboarding churn or retention? And what is the usage turn and retention? That is what you are seeing, that these two are really, really different. Now onboarding churn, involves the buyer's remorse, you know may have been a wrong sell, are less, should not be accounted necessarily to the customer success organization. They may very much relate to the sales process. Whereas, the logo churn, license churn, and revenue churn, license refers to the seats. Logo refers to obviously the entire client being lost. Revenue leads to the revenue per client being decreased. And licensed means like, hey, I'm losing seats. My average revenue per seat is going up. So I don't have revenue churn, but I got fewer seats to, you know, make an impact on their business. These are three very different metrics. It gives a very different definition. We are looking closer at the resolution that we're going through. I need to make sure that you understand, that we measure churn. Churn is often like 2%, 3%. And we are measuring this as part of our calculations as retention. Not at worse, 4% churn equates 96% retention. One minus churn retention. In order to put it all in the same mathematical domain. The same we see here at the end. Expansion, upsell growth, and pretty much always similar kind of term for describing am I selling more? Am I creating more impact for my client? When we take a closer look, we referred to that metric as CR7. The growth metric, the expansion metric. And it is defined in four different ways of growing. You get renewing, same contract, same decision-maker. Reselling, same contract, new decision-maker. Upselling, same person selling more stuff, same department selling more stuff. And cross-selling, selling to other departments. Four very different metrics. Now, if you're running a $2-$3 million recurring revenue operation, this is all the same. But if you're generating 60, 70, $80 million of revenue a year, or just for a shock and awe, a month, then these metrics have different departments, different organizations, different, you know, like like ways of managing them. I want you to think about that. What you see down here, is the old and the new form of data, of conversion metrics, side by side. Where you see that the refined customer success metrics, have a lot more detail to them than just churn and upsell. That's the point. There's a lot more to it. Those creates the conversion metrics. And we refer to them as conversion rates CR1 to CR7. This creates a data model in which these three metrics look like this. And this is always, once you use this model, we can, as you'll see in the next model that we're gonna describe in the next video, in the near future, I'm gonna show you that I can now apply mathematical formulas, based on this model. If I don't have the data model, I cannot apply mathematical formulas. Now, what you see here is I what I'm gonna next. And the final part is, I'm gonna step in, and we're going to talk a little bit about what can we do? What are the findings that we have, okay? Wooh! Let's stretch. Gosh. My neck is getting stiff. Let's do this. I'm ready. You ready? Are you ready? Wooh! The last part of this video. We're gonna go into three specific cases. We're just gonna start off with benchmark data. Benchmark compare. Here we go. What we now have, because we have the data model, we can start comparing customers against each other. And what we noticed is that based on annual contract value depicted here on the left, we noticed that there are certain trends. These trends can now be observed and can be applied. That there. So annual contract value of $10,000 versus $100,000 has different conversion rates. Okay? Now take a look at that, as I explain what happens here. What you'll see down here is that the conversion rate is mapped through awareness and education. And these are the two metrics I said before. Now, what it creates, it creates typical annual contract territory, anywhere from 20,000 to all these large dollar values, that's annual contract. Now, what you see here, is in those annual contracts what you are expected in conversion rates. All the way from CR1 to CR2. And if you see down there CR3 and CR4, with the subtitling here at the bottom indicating handoff and win rate. There you have it. Yes, yes, yes. That's what we're doing here. Okay? Now those are typical annual contracts. What I'm going to do next here, is I'm going to also say, hey, those annual contracts, they in generally are exponential goal. if I explain like next time, but here, where is territory for compound impact, is these contracts that come in at the lower ACV. That is where you see compound impact territory. Primarily because the renewal cycle is monthly. Therefore, if I compound these things, I compound them per month. So a three-year contract compounds 36 times, versus an annual contract, which compounds over three years at the compound factor of three. So, that is that benchmark. The key down here is we can compare where you're at. We're gonna come back to that in a little bit. Now, what we're going to do is I'm now gonna apply this data model to different go-to market models. I'm gonna show you some of the findings that we are now seeing, based on his data model. Now, I was struck the other day, when I noticed that I saw a blueprint, how ,yeah, for me these two things start to look very similar, right? That you know, like, and I know it may not, you gonna like, Jacco, you're a little like, what? Say what? You know you're little like, looped too little because you may not see it. But I see these things as being very similar. So having done that, I just thought that I, you know, like share with you some of what we see down there. Okay. If I see that I'm gonna say, I'm gonna only take a look at the acquisition because I gotta, I need some space on the right here, okay? So on the right, I'm gonna use some space. But now what I'm going to depict is a standard go-to market model. I'm gonna create volume, use of volume metrics, in a one-stage sales organization. My marketing campaign is measuring volume of MQL. Very standard, very straightforward. Then I'm gonna qualify those MQLs. I'm gonna put them through a disco demo, and what I'm measuring key performance indicators are, volume of demos, and conversion of MQL into commit. Now these are good metrics. I may even start measuring if I now turn. And look, I'm turning into two-stage sales organization. Now my SDRs in this case, you know, I have one group that is gonna qualify those leads and one group, that's gonna close them. Get them to a commitment. Okay? You see down here, conversion is split up. And so now measuring my MQL to SQL metrics, my conversion rate there. And my conversion rate of SQL to wins. Then because I noticed that there's a handoff, I give them a little bit of handle right now. Look at what I'm measuring on the right. I'm measuring volume of MQLs, volume of demos provided, conversion rate, and hand off rate. These become my key matrices. These are how I'm gonna measure performance indicators. And as I, you know, like go further to the right, I may even think about like, hey, I'm gonna do outbound prospecting. No longer am I gonna go inbound. From here, I'm gonna go outbound. When I go outbound, I'm gonna create, you know, number of emails and calls. Look at the top. I mean, I'm adding new metrics. Number of emails and calls, and measuring engagement of clients. And as I work in order to target the right companies, in order to make sure I address them, I'm gonna identify those. Then once I have identified them, I'm gonna pre-qualify. I'm gonna do that by doing research. And the research that I'm doing on, is I'm learning from the existing demos I've provided. Now look at that again, I'm gonna go to the left or to the right, key performance indicators. Prospects identified, prospects qualified, prospects research. These are all become key performance indicators. Look at the list that is growing. Now, I'm gonna reach out to those people. Number of emails and call sent. Does this start to feel familiar? That you start to see, this is a volume based outbound organization. Now what I'm going to do, I'm gonna make sure that I'm measuring the number of meetings set. So I'm gonna outreach. And I'm gonna make sure that the discoveries are set. What some of you found out, is that, hey, if I don't research, if I just start spamming my clients with volume of leads, I'm just spamming them with emails, I don't need the research. I don't need to identify. I'm just giving them emails. And so I skip the identification and research. I just, as I reached out to them, I qualified them. When they respond to me, I only spend time with them when they approach me. Right? And then I qualify. Now what I'm doing is, what we found is by inserting or what the world found, by inserting an automatic calendaring tool link in there. Why do I even have a qualification? Dude, if you wanna discover me, meet? Let's go do it. So this approach has created, I no longer need to look at the engagement of volume of MQL. I'm just looking at the amount of meetings set. Now, while I do that, you know, my salespeople are now responsible for, you know, getting that commitment for the logo's won. And what you see down here, is a typical outbound, improper, not the right way, kind of sales organization of key performance indicators. How many emails per calls per week? How many meetings set? And how many deals won? And then we're gonna add an incentive program for this, in order to make this even worse, okay? Now, look, this is outdated. We may as well put, you know, like this kind of music to it, okay? I just wanna let it sit in, how we went through it. I'm gonna skip through it, okay? As you listened to the music, I'm gonna replay this, okay? Let's rewind. You see. It keeps going wrong. Again and again. I can literally hit rewind, and do it again. Then we end up with the same result. Okay? This for most organizations, won't work. Okay. So we need something new for that. And that's, you know, like that is what the program that we are seeing more and more today, the things that we work on in an effort to improve. Okay? So that isn't a clear, noticeable thing. And many of you who are at this point then go like, yeah, yeah. Yeah. I hear you. I hear you. It is painful. Yes, yes, yes. We'll get through it, don't worry. We're all here. It's gonna get better. Now what we're gonna see with the new GTM approaches, and think of content-led growth, product-led growth, or research-led growth, what we're really targeting, right? You'll see that those organizations actually increase the effort. And so, with a content lead growth, think of that as word of mouth. We are targeting content. And as clients engage with their cons, or content, their content come in as an inbound. That inbound acts and behaves, as a self qualification. They researched the content. Because they come inbound, the calendaring function now takes place semi-automatically. It could be a response via an email, it could be automatic, but they are interested. They qualify. This is what we see. For example, product led-growth organizations. Why they are doing this really well. In this case, it is the assistant product-led growth, where a lead comes in and an insights sales wrap up, pick up the process, but that is not needed. We see more and more that this process, if the client really wants to buy, and if the commitment is within reason, they will go through the entire process. And it automatically creates, and give room to the product-led growth. Now, product-led growth and content-led growth, go really well hand in hand, meaning I have lots of interesting content that is driving people to take a look at the product. These two, are like two peas in a pod. That is how we can look at all this volume and conversion metric, and how we can now explain things, measure and see why we are doing certain things and how we have to create certain performance indicators or do the wrong thing. Create the wrong performance indicators and cause the wrong action. Right now what I'm doing is advanced. It is what most of you will not do. Not in a while. But it's so fun. Whoo! Sorry. I'm just having fun. Sorry. Let's get back Jacco. Get back. Say your track. Okay. Last and final one. This is the fun part. This is the payoff. This is where the future goes. This is where in five years, 10 years, 50 years from now, what I aspire, what I dream, what I hope with my entire heart. How we are gonna teach sales at the universitary level. Okay? You know, like we're not gonna teach closing and outbound code call. That is not gonna be a skill that we need, you know, like graduate level interest. Okay. What we see down here, is in this case we're gonna define win rate as a conversion. In this case, from a sales qualified lead into a win. I'm gonna keep it simple. What we see here are two cases. Rob, who turns in 30 SQLs, and he turns them into 10 deals per quarter, with 20 days sales cycle. And we're got to compare that, against, in this particular case, with a win rate of 33% sale cycles 20 days, with an average MRR of, new level of MRR of $50,000. If you compare that the against Mary, Mary turns 30 SQLs into six deals, significantly fewer. Therefore, her win rate is 20%. She also has a sales cycle, a sales price of 5k, but she uses a few more days, 28 days. So if you see right now, if you have to fire one, or if you still have to say like, hey, I can only keep one of them. Most people would keep, based on standard volume metrics, and conversion metrics. Volume metrics being, in this case Rob generates more MRR, and has a better win rate. And his sales cycle is shorter. Based on these three metrics I gave you, you're gonna say, hey, we've gotta keep Rob. And so we're gonna let go of Mary. This however proves not to be the case. Because if we now started taking into account, what happened to the churn at the back end? We see that Rob actually, his churn, he churned 50% of all the deals. That means half of his deals churned. That means that the new MRR per month was reduced to $25,000. And, but on the other hand, and this, you know, like phantom case, Mary's deal did not turn. Why? Mary spent a little bit more time with them. Listened more, and made sure that the deals she closed, that she got commitment on, essentially resulted in those clients actually wanting them. And here dare 40 cases. Mary should not be let go either. I'm not saying one or the other. I'm just making a point down here, is both are doing something good. We still like that Rob, you know, turns a lot of deals, but we may wanna tune that. And we may wanna tune as well, Mary, that she's closes a little faster, so that both are within reason. But it points out to you, that there is a metric. What happens here is, we are comparing two conversion rates. Two! Dos! Two. Two conversion metrics. And when we compare them against each other, we are gonna get performance metrics. I'm gonna explain this in detail because this folks, this is like the world of growth for the next, like I said, decade worth of sales processes. What we see down here, is I'm gonna take that conversion rate four, which is the win rate. I'm gonna put that on that axis. And I'm gonna put the win rate, the churn, on that horizontal axis. Okay? This creates a two by two. Now, what I'm gonna do in this two by two, I'm gonna assume an average contract value of $24,000. Now, I'm gonna go into my benchmark data which I copied here for ease of understanding. And I'm gonna say at $24,000, it fits in the bracket of ACV $20k. In that, I now know that my conversion rate, I'm gonna pull that out of there in that benchmark. And that says, on average, that middle line should be at 22%. So I'm gonna enter that 22% in there. And I'm gonna get what is below average. Oh, well blow 22%. So, you know, 10%. And what is above average, 30%, right? So, I now know there's something below and something above. Now, what I'm going to do, is I'm gonna have to say, it's like, hey, that's conversion rate number four, I'm gonna point that it came in, what we measured our conversion rate, you know, phantom created here, not reality. But phantom is, hey, we have a conversion rate ourselves of 18%. That is what we measured. We have a win rate. We win, one out of approximately every five deals. And so what we see now here is that that fits below average. What I'm now going to do, I'm going to take a look at our churn metrics. How much of these clients are properly onboarded. Well, we see that seven out of a hundred clients. Yeah. Like they stopped being onboarded. They exit out of the onboarding process, and they want their money back. In retention metrics that therefore is 93%, 7% churn on an annual platform. Now, what I see here is that the norm at that price is 96%. And so I'm gonna fill in 96%. I'm gonna say we're at 93%. So as I put in 93%, it shows me I am below average. I'm below average on my I churn, and therefore I'm not doing good. And I'm below average on my win rate. So I'm sitting into that quadrant. Now I know where I'm at. Let that sit in. I noticed because of the benchmark, and because of the metrics and of the data. Because we're all measuring the same data, we can now compare with each other. I can now compare apples to apples, so to speak. Now, what you'll see is, I'm now gonna turn, like what you think was, you know, I started off with magic, right? And how bad that magic was. I'm now gonna turn science and magic. They're the same thing, but science is real. Okay? It's like magic, but it's real. Okay. So what I'm gonna do down here, I want to depict to you what I can do right now. This is like, I hope you enjoyed this as much, learning from this as I love sharing it with you. If I know that the below average win rate, and a below average conversion rate fits in that scenario, then I now know what to do there. I can establish over time that if I, my win rate is low and my retention is low, that I need to look at having a go to market problem first because I'm not winning the right deals potentially. Are we selling into the right market? Are we promoting the right impact we offer. If we're not, we're gonna see that we're in this category. So, I'm gonna point upstream and say like, hey, folks, we are having a problem, that our pipeline sourcing is not coming from the right kind of clients. And that is most likely, it happens a lot. Oh, we just went to a trade show and we got a whole bunch of like flaky leads in there that went through the pipeline. And as they, the proverbial, the S word in the funnel leads to the S word coming out of the funnel. Now, if I look further to the right, I see that retention is still below average. But I'm winning above average. That means like, hey, I'm winning a lot of deals, but I'm winning a little bit to money. Like what we saw with Rob being in the case. We're winning the wrong kind of deals. Client seems to be in a hurry, which is a customer success problem. Or they have buyer's remorse. They didn't really bought what they wanted. And so I know what to do there. If I look at scenario three, we have a below average win rate. And we have an, you know, a good six, retention, below average attention. We see that we were winning the right customers, but not enough. It all comes down to here or to the right. And it says like, hey, if we are having successful churn and so on, that is what we really want. We wanna get to that scenario four. That creates four scenarios. These four scenarios, can be compared not only in this specific case, but they can be compared in all kinds of, I can measure MQLs against win rate. I can measure a hand off of the SDR, against the win rate and so on. I can see things. These are all different performance metrics, that will tell me what I need to do in the process. So if I occur in that situation, then this is the most likely outcome I need to take. The reason I say all these, I dropped earlier on, the word artificial intelligence. The moment in time, I create these closed loop systems, because that's what they're doing, I essentially be ready for artificial intelligence. This allows to growth in the future. That's to me, we can now, like, I can teach this, you can measure this. We can repeat this. We can improve this. We can do so many things with this. This is just the opening of all the things we can do. The entire world is open to us. Okay? ♪ Where do we go from, where do we go from ♪ So in summary, ♪ No one can save us, ♪ ♪ Save us from keeping clear ♪ Here is your day tomorrow. ♪ I don't wanna lose you ♪ Just measure. Think of this data model. This allows you to rethink all your ways. You know, like measure the right thing, do the right thing. Convert the right thing. And that was it for the data model. ♪ Hey, hey, hey ♪ ♪ I just wanna say you are my new crave ♪ ♪ Hey, hey, hey ♪ ♪ I just wanna say you are my new crave ♪ Next one up is the mathematical model. We will launch this. I have it already created. I just need to create the video around it. But I have all the material ready. Give me one week to two weeks and we'll launch this. ♪ Hey, hey, hey ♪ ♪ I just wanna say you are my new crave ♪ Whoo! I am just excited that I can share this with you. I'm looking forward and hope that you are as excited, to have as much fun with me, as I'm having, giving it to you. And with that, I want to let you go. Wanna wish you a happy, happy time. I wanna thank you all for being here, and looking forward to see you on the next session. ♪♪♪

Learn how to Architect Your Revenue using the Recurring Revenue Operating Model

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The data model itself is straightforward; the key is to understand how the model is built to support growth loops, closed loops systems, and revenue processes.

The topics that we step through in this workshop include:

  1. The bowtie as a full-funnel model
  2. How the bowtie supports growth loops, and the need to create a closed-loop system
  3. A customer-centric data model based on customers achieving recurring impact, which then results in recurring revenue
  4. The three types of metrics that every recurring revenue team should be measuring: volume metrics, time metrics, and conversion metrics

Additional insights and key findings from this workshop: 

a) how to use benchmark data and apply it to your own model

b) the application of various GTM models and associated metrics

c) how to use performance metrics in practice

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